SPdel notebook example file¶

In [1]:
import SPdel
import os
In [2]:
fasta = './data/Megaleporinus/Megaleporinus_COI.fasta'
tree = './data/Megaleporinus/Megaleporinus_tree.nwk'
basepath=os.path.dirname(fasta)
Inputs=SPdel.reading_data(fasta,tree)

############################################################################

SPdel v2.0 - Species delimitation and statistics for DNA Barcoding data sets

############################################################################

Sequences are aligned (same size)
Fasta file with 116 sequences and 600 base pairs

Analyzing data using nominal delimitation¶

In [3]:
nominal=SPdel.run_nominal(basepath,Inputs)
#####################
Nominal MOTUs
#####################

#####LS_brn#####
LS_brn_L930, LS_brn_L931, LS_brn_L932

#####LS_con#####
LS_con_L210, LS_con_L211, LS_con_L286, LS_con_L291, LS_con_L292, LS_con_L820

#####LS_elo#####
LS_elo_L1041, LS_elo_L1046, LS_elo_L1047, LS_elo_L287, LS_elo_L300, LS_elo_L305, LS_elo_L307, LS_elo_L308, LS_elo_L309

#####LS_gar#####
LS_gar_L293, LS_gar_L294, LS_gar_L295, LS_gar_L296, LS_gar_L298

#####LS_mac#####
LS_mac_B061, LS_mac_B082, LS_mac_B086, LS_mac_B087, LS_mac_B088, LS_mac_B089, LS_mac_L083, LS_mac_L085, LS_mac_L178, LS_mac_L212, LS_mac_L225, LS_mac_L290, LS_mac_L890, LS_mac_L891

#####LS_muy#####
LS_muy_L907, LS_muy_L913, LS_muy_L914, LS_muy_L915

#####LS_obt#####
LS_obt_B031, LS_obt_B070, LS_obt_B071, LS_obt_B074, LS_obt_B075, LS_obt_B077, LS_obt_B090, LS_obt_B100, LS_obt_B101, LS_obt_B102, LS_obt_B103, LS_obt_L004, LS_obt_L007, LS_obt_L008, LS_obt_L009, LS_obt_L013, LS_obt_L016, LS_obt_L084, LS_obt_L253, LS_obt_L266, LS_obt_L267, LS_obt_L268, LS_obt_L269, LS_obt_L282, LS_obt_L283, LS_obt_L314, LS_obt_L315, LS_obt_L316, LS_obt_L320, LS_obt_L547, LS_obt_L548

#####LS_piv#####
LS_piv_B060, LS_piv_B076, LS_piv_B078, LS_piv_B093, LS_piv_B094, LS_piv_B095, LS_piv_B096, LS_piv_B097, LS_piv_B098, LS_piv_B099, LS_piv_B140, LS_piv_B141, LS_piv_B142, LS_piv_B144, LS_piv_L002, LS_piv_L003, LS_piv_L005, LS_piv_L006, LS_piv_L010, LS_piv_L011, LS_piv_L014, LS_piv_L284, LS_piv_L371

#####LS_rei#####
LS_rei_B072, LS_rei_B073, LS_rei_L338, LS_rei_L339, LS_rei_L341, LS_rei_L342, LS_rei_L343, LS_rei_L353, LS_rei_L355, LS_rei_L773, LS_rei_L777, LS_rei_L778, LS_rei_L779

#####LS_tri#####
LS_tri_L179, LS_tri_L180, LS_tri_L182, LS_tri_L519, LS_tri_L618, LS_tri_L621, LS_tri_L690, LS_tri_L955


Using k2p distance

In [4]:
nominal.print_summary()
Out[4]:
Mean Max NN DtoNN
LS_brn 0.000000 0.00000 LS_obt 6.77516
LS_con 2.127067 3.98825 LS_obt 5.60360
LS_elo 0.037100 0.16695 LS_obt 2.73593
LS_gar 0.000000 0.00000 LS_obt 7.68126
LS_mac 0.903538 1.85854 LS_tri 4.51779
LS_muy 7.655915 15.31183 LS_tri 7.47916
LS_obt 1.937511 6.71724 LS_elo 2.73593
LS_piv 0.266286 1.00758 LS_obt 2.90372
LS_rei 0.316828 0.70177 LS_con 6.14484
LS_tri 3.392014 6.33176 LS_mac 4.51779

Analyzing data using PTP species delimitation¶

In [5]:
PTP=SPdel.run_PTP(basepath,Inputs)
Speciation rate: 43.602
Coalesecnt rate: 1666.347
Null logl: 959.787
MAX logl: 1249.664
P-value: 0.000
Kolmogorov-Smirnov test for model fitting:
Speciation: Dtest = 0.539 p-value >= 0.1 excellent model fitting
Coalescent: Dtest = 2.220 p-value < 0.01 poor model fitting
Number of species: 18


#####################
PTP MOTUs
#####################

#####MOTU_01#####
LS_muy_L913, LS_muy_L915, LS_muy_L914

#####MOTU_02#####
LS_muy_L907

#####MOTU_03#####
LS_brn_L930, LS_brn_L931, LS_brn_L932

#####MOTU_04#####
LS_gar_L293, LS_gar_L298, LS_gar_L294, LS_gar_L296, LS_gar_L295

#####MOTU_05#####
LS_tri_L179, LS_tri_L180, LS_tri_L182

#####MOTU_06#####
LS_con_L286, LS_con_L820, LS_con_L291, LS_con_L292

#####MOTU_07#####
LS_con_L210, LS_con_L211

#####MOTU_08#####
LS_tri_L519, LS_tri_L690, LS_tri_L618, LS_tri_L955, LS_tri_L621

#####MOTU_09#####
LS_obt_B074, LS_obt_L016, LS_obt_B077, LS_obt_B075, LS_obt_L009, LS_obt_L548, LS_obt_L004, LS_obt_L013, LS_obt_L283, LS_obt_L282, LS_obt_L547, LS_obt_L007, LS_obt_L008, LS_obt_B100, LS_obt_B103, LS_obt_B101, LS_obt_B102

#####MOTU_10#####
LS_elo_L1041, LS_elo_L287, LS_elo_L309, LS_elo_L1046, LS_elo_L300, LS_elo_L305, LS_elo_L307, LS_elo_L308, LS_elo_L1047

#####MOTU_11#####
LS_obt_B031, LS_obt_B090, LS_obt_B070, LS_obt_L268, LS_obt_L266, LS_obt_L316, LS_obt_B071, LS_obt_L267, LS_obt_L269, LS_obt_L253, LS_obt_L314, LS_obt_L315, LS_obt_L320

#####MOTU_12#####
LS_obt_L084

#####MOTU_13#####
LS_mac_B061, LS_mac_B086, LS_mac_B089, LS_mac_B087, LS_mac_B088

#####MOTU_14#####
LS_mac_B082, LS_mac_L890, LS_mac_L083, LS_mac_L085, LS_mac_L178, LS_mac_L225, LS_mac_L212, LS_mac_L891, LS_mac_L290

#####MOTU_15#####
LS_rei_L773, LS_rei_L777, LS_rei_L778, LS_rei_L779

#####MOTU_16#####
LS_rei_B072, LS_rei_L342, LS_rei_B073, LS_rei_L341, LS_rei_L338, LS_rei_L355, LS_rei_L339, LS_rei_L343, LS_rei_L353

#####MOTU_17#####
LS_piv_B140, LS_piv_B141, LS_piv_B142, LS_piv_B144

#####MOTU_18#####
LS_piv_B060, LS_piv_B095, LS_piv_B093, LS_piv_L002, LS_piv_L003, LS_piv_L011, LS_piv_L010, LS_piv_B076, LS_piv_B094, LS_piv_L284, LS_piv_L371, LS_piv_B078, LS_piv_L005, LS_piv_L006, LS_piv_L014, LS_piv_B096, LS_piv_B097, LS_piv_B098, LS_piv_B099


Using k2p distance

In [6]:
PTP.print_summary()
Out[6]:
Mean Max NN DtoNN
MOTU_01 0.000000 0.00000 MOTU_03 11.60407
MOTU_02 NaN NaN MOTU_08 7.47916
MOTU_03 0.000000 0.00000 MOTU_09 6.77516
MOTU_04 0.000000 0.00000 MOTU_09 7.68126
MOTU_05 0.000000 0.00000 MOTU_08 6.33176
MOTU_06 0.000000 0.00000 MOTU_07 3.98825
MOTU_07 0.000000 0.00000 MOTU_06 3.98825
MOTU_08 0.000000 0.00000 MOTU_14 4.51779
MOTU_09 0.143081 0.50167 MOTU_11 2.84291
MOTU_10 0.037100 0.16695 MOTU_11 2.73593
MOTU_11 0.000000 0.00000 MOTU_10 2.73593
MOTU_12 NaN NaN MOTU_17 2.90372
MOTU_13 0.136404 0.34101 MOTU_14 1.55005
MOTU_14 0.000000 0.00000 MOTU_13 1.55005
MOTU_15 0.000000 0.00000 MOTU_16 0.67115
MOTU_16 0.000000 0.00000 MOTU_15 0.67115
MOTU_17 0.083475 0.16695 MOTU_18 0.67024
MOTU_18 0.058574 0.16772 MOTU_17 0.67024

Analyzing data using bPTP species delimitation¶

In [7]:
bPTP=SPdel.run_bPTP(basepath,Inputs)
Estimated number of species is between 17 and 21
Mean: 18.56

bPTP finished running with the following parameters:
 MCMC iterations:................10000
 MCMC sampling interval:.........100
 MCMC burn-in:...................0.10
 MCMC seed:......................1234


#####################
bPTP MOTUs
#####################

#####MOTU_01#####
LS_muy_L913, LS_muy_L915, LS_muy_L914

#####MOTU_02#####
LS_muy_L907

#####MOTU_03#####
LS_brn_L930, LS_brn_L931, LS_brn_L932

#####MOTU_04#####
LS_gar_L293, LS_gar_L298, LS_gar_L294, LS_gar_L296, LS_gar_L295

#####MOTU_05#####
LS_tri_L179, LS_tri_L180, LS_tri_L182

#####MOTU_06#####
LS_con_L286, LS_con_L820, LS_con_L291, LS_con_L292

#####MOTU_07#####
LS_con_L210, LS_con_L211

#####MOTU_08#####
LS_tri_L519, LS_tri_L690, LS_tri_L618, LS_tri_L955, LS_tri_L621

#####MOTU_09#####
LS_obt_B074, LS_obt_L016, LS_obt_B077, LS_obt_B075, LS_obt_L009, LS_obt_L548, LS_obt_L004, LS_obt_L013, LS_obt_L283, LS_obt_L282, LS_obt_L547, LS_obt_L007, LS_obt_L008, LS_obt_B100, LS_obt_B103, LS_obt_B101, LS_obt_B102

#####MOTU_10#####
LS_elo_L1041, LS_elo_L287, LS_elo_L309, LS_elo_L1046, LS_elo_L300, LS_elo_L305, LS_elo_L307, LS_elo_L308, LS_elo_L1047

#####MOTU_11#####
LS_obt_B031, LS_obt_B090, LS_obt_B070, LS_obt_L268, LS_obt_L266, LS_obt_L316, LS_obt_B071, LS_obt_L267, LS_obt_L269, LS_obt_L253, LS_obt_L314, LS_obt_L315, LS_obt_L320

#####MOTU_12#####
LS_obt_L084

#####MOTU_13#####
LS_mac_B061, LS_mac_B086, LS_mac_B089, LS_mac_B087, LS_mac_B088

#####MOTU_14#####
LS_mac_B082, LS_mac_L890, LS_mac_L083, LS_mac_L085, LS_mac_L178, LS_mac_L225, LS_mac_L212, LS_mac_L891, LS_mac_L290

#####MOTU_15#####
LS_rei_L773, LS_rei_L777, LS_rei_L778, LS_rei_L779

#####MOTU_16#####
LS_rei_B072, LS_rei_L342, LS_rei_B073, LS_rei_L341, LS_rei_L338, LS_rei_L355, LS_rei_L339, LS_rei_L343, LS_rei_L353

#####MOTU_17#####
LS_piv_B140, LS_piv_B141, LS_piv_B142, LS_piv_B144

#####MOTU_18#####
LS_piv_B060, LS_piv_B095, LS_piv_B093, LS_piv_L002, LS_piv_L003, LS_piv_L011, LS_piv_L010, LS_piv_B076, LS_piv_B094, LS_piv_L284, LS_piv_L371, LS_piv_B078, LS_piv_L005, LS_piv_L006, LS_piv_L014, LS_piv_B096, LS_piv_B097, LS_piv_B098, LS_piv_B099


Using k2p distance

<Figure size 640x480 with 0 Axes>
In [8]:
bPTP.print_summary()
Out[8]:
Mean Max NN DtoNN
MOTU_01 0.000000 0.00000 MOTU_03 11.60407
MOTU_02 NaN NaN MOTU_08 7.47916
MOTU_03 0.000000 0.00000 MOTU_09 6.77516
MOTU_04 0.000000 0.00000 MOTU_09 7.68126
MOTU_05 0.000000 0.00000 MOTU_08 6.33176
MOTU_06 0.000000 0.00000 MOTU_07 3.98825
MOTU_07 0.000000 0.00000 MOTU_06 3.98825
MOTU_08 0.000000 0.00000 MOTU_14 4.51779
MOTU_09 0.143081 0.50167 MOTU_11 2.84291
MOTU_10 0.037100 0.16695 MOTU_11 2.73593
MOTU_11 0.000000 0.00000 MOTU_10 2.73593
MOTU_12 NaN NaN MOTU_17 2.90372
MOTU_13 0.136404 0.34101 MOTU_14 1.55005
MOTU_14 0.000000 0.00000 MOTU_13 1.55005
MOTU_15 0.000000 0.00000 MOTU_16 0.67115
MOTU_16 0.000000 0.00000 MOTU_15 0.67115
MOTU_17 0.083475 0.16695 MOTU_18 0.67024
MOTU_18 0.058574 0.16772 MOTU_17 0.67024

Analyzing data using mPTP species delimitation¶

Another method included in SPdel is the Multi-rate Poisson tree processes - mPTP (Kapli, et al. 2016). Of course, you can obtain all same metrics and figures as previous methods

In [9]:
mPTP=SPdel.run_mPTP(basepath,Inputs)
#####################
mPTP MOTUs
#####################

#####MOTU_01#####
LS_con_L286, LS_con_L820, LS_con_L291, LS_con_L292

#####MOTU_02#####
LS_con_L210, LS_con_L211

#####MOTU_03#####
LS_brn_L930, LS_brn_L931, LS_brn_L932

#####MOTU_04#####
LS_elo_L1041, LS_elo_L287, LS_elo_L309, LS_elo_L1046, LS_elo_L300, LS_elo_L305, LS_elo_L307, LS_elo_L308, LS_elo_L1047

#####MOTU_05#####
LS_obt_B031, LS_obt_B090, LS_obt_B070, LS_obt_L268, LS_obt_L266, LS_obt_L316, LS_obt_B071, LS_obt_L267, LS_obt_L269, LS_obt_L253, LS_obt_L314, LS_obt_L315, LS_obt_L320

#####MOTU_06#####
LS_obt_B074, LS_obt_L016, LS_obt_B077, LS_obt_B075, LS_obt_L009, LS_obt_L548, LS_obt_L004, LS_obt_L013, LS_obt_L283, LS_obt_L282, LS_obt_L547, LS_obt_L007, LS_obt_L008, LS_obt_B100, LS_obt_B103, LS_obt_B101, LS_obt_B102

#####MOTU_07#####
LS_piv_B140, LS_piv_B141, LS_piv_B142, LS_piv_B144, LS_piv_B060, LS_piv_B095, LS_piv_B093, LS_piv_L002, LS_piv_L003, LS_piv_L011, LS_piv_L010, LS_piv_B076, LS_piv_B094, LS_piv_L284, LS_piv_L371, LS_piv_B078, LS_piv_L005, LS_piv_L006, LS_piv_L014, LS_piv_B096, LS_piv_B097, LS_piv_B098, LS_piv_B099

#####MOTU_08#####
LS_obt_L084

#####MOTU_09#####
LS_gar_L293, LS_gar_L298, LS_gar_L294, LS_gar_L296, LS_gar_L295

#####MOTU_10#####
LS_rei_L773, LS_rei_L777, LS_rei_L778, LS_rei_L779

#####MOTU_11#####
LS_rei_B072, LS_rei_L342, LS_rei_B073, LS_rei_L341, LS_rei_L338, LS_rei_L355, LS_rei_L339, LS_rei_L343, LS_rei_L353

#####MOTU_12#####
LS_muy_L913, LS_muy_L915, LS_muy_L914

#####MOTU_13#####
LS_muy_L907

#####MOTU_14#####
LS_tri_L179, LS_tri_L180, LS_tri_L182

#####MOTU_15#####
LS_mac_B061, LS_mac_B086, LS_mac_B089, LS_mac_B087, LS_mac_B088

#####MOTU_16#####
LS_mac_B082, LS_mac_L890, LS_mac_L083, LS_mac_L085, LS_mac_L178, LS_mac_L225, LS_mac_L212, LS_mac_L891, LS_mac_L290

#####MOTU_17#####
LS_tri_L519, LS_tri_L690, LS_tri_L618, LS_tri_L955, LS_tri_L621


Using k2p distance

In [10]:
mPTP.print_summary()
Out[10]:
Mean Max NN DtoNN
MOTU_01 0.000000 0.00000 MOTU_02 3.98825
MOTU_02 0.000000 0.00000 MOTU_01 3.98825
MOTU_03 0.000000 0.00000 MOTU_06 6.77516
MOTU_04 0.037100 0.16695 MOTU_05 2.73593
MOTU_05 0.000000 0.00000 MOTU_04 2.73593
MOTU_06 0.143081 0.50167 MOTU_05 2.84291
MOTU_07 0.266286 1.00758 MOTU_08 2.90372
MOTU_08 NaN NaN MOTU_07 2.90372
MOTU_09 0.000000 0.00000 MOTU_06 7.68126
MOTU_10 0.000000 0.00000 MOTU_11 0.67115
MOTU_11 0.000000 0.00000 MOTU_10 0.67115
MOTU_12 0.000000 0.00000 MOTU_03 11.60407
MOTU_13 NaN NaN MOTU_17 7.47916
MOTU_14 0.000000 0.00000 MOTU_17 6.33176
MOTU_15 0.136404 0.34101 MOTU_16 1.55005
MOTU_16 0.000000 0.00000 MOTU_15 1.55005
MOTU_17 0.000000 0.00000 MOTU_16 4.51779

Analyzing data using GMYC species delimitation¶

In [11]:
GMYC=SPdel.run_GMYC(basepath,Inputs)
Highest llh:1004.3909296154683
Num spe:18
Null llh:968.4341056152681
P-value:2.220446049250313e-16
Final number of estimated species by GMYC: 18

#####################
GMYC MOTUs
#####################

#####MOTU_01#####
LS_obt_B074, LS_obt_L016, LS_obt_B077, LS_obt_B075, LS_obt_L009, LS_obt_L548, LS_obt_L004, LS_obt_L013, LS_obt_L283, LS_obt_L282, LS_obt_L547, LS_obt_L007, LS_obt_L008, LS_obt_B100, LS_obt_B103, LS_obt_B101, LS_obt_B102

#####MOTU_02#####
LS_piv_B060, LS_piv_B095, LS_piv_B093, LS_piv_L002, LS_piv_L003, LS_piv_L011, LS_piv_L010, LS_piv_B076, LS_piv_B094, LS_piv_L284, LS_piv_L371, LS_piv_B078, LS_piv_L005, LS_piv_L006, LS_piv_L014, LS_piv_B096, LS_piv_B097, LS_piv_B098, LS_piv_B099

#####MOTU_03#####
LS_mac_B082, LS_mac_L890, LS_mac_L083, LS_mac_L085, LS_mac_L178, LS_mac_L225, LS_mac_L212, LS_mac_L891, LS_mac_L290

#####MOTU_04#####
LS_obt_B031, LS_obt_B090, LS_obt_B070, LS_obt_L268, LS_obt_L266, LS_obt_L316, LS_obt_B071, LS_obt_L267, LS_obt_L269, LS_obt_L253, LS_obt_L314, LS_obt_L315, LS_obt_L320

#####MOTU_05#####
LS_mac_B061, LS_mac_B086, LS_mac_B089, LS_mac_B087, LS_mac_B088

#####MOTU_06#####
LS_elo_L1041, LS_elo_L287, LS_elo_L309, LS_elo_L1046, LS_elo_L300, LS_elo_L305, LS_elo_L307, LS_elo_L308, LS_elo_L1047

#####MOTU_07#####
LS_rei_B072, LS_rei_L342, LS_rei_B073, LS_rei_L341, LS_rei_L338, LS_rei_L355, LS_rei_L339, LS_rei_L343, LS_rei_L353

#####MOTU_08#####
LS_tri_L519, LS_tri_L690, LS_tri_L618, LS_tri_L955, LS_tri_L621

#####MOTU_09#####
LS_gar_L293, LS_gar_L298, LS_gar_L294, LS_gar_L296, LS_gar_L295

#####MOTU_10#####
LS_piv_B140, LS_piv_B141, LS_piv_B142, LS_piv_B144

#####MOTU_11#####
LS_con_L286, LS_con_L820, LS_con_L291, LS_con_L292

#####MOTU_12#####
LS_rei_L773, LS_rei_L777, LS_rei_L778, LS_rei_L779

#####MOTU_13#####
LS_tri_L179, LS_tri_L180, LS_tri_L182

#####MOTU_14#####
LS_muy_L913, LS_muy_L915, LS_muy_L914

#####MOTU_15#####
LS_brn_L930, LS_brn_L931, LS_brn_L932

#####MOTU_16#####
LS_con_L210, LS_con_L211

#####MOTU_17#####
LS_obt_L084

#####MOTU_18#####
LS_muy_L907


Using k2p distance

In [12]:
GMYC.print_summary()
Out[12]:
Mean Max NN DtoNN
MOTU_01 0.143081 0.50167 MOTU_04 2.84291
MOTU_02 0.058574 0.16772 MOTU_10 0.67024
MOTU_03 0.000000 0.00000 MOTU_05 1.55005
MOTU_04 0.000000 0.00000 MOTU_06 2.73593
MOTU_05 0.136404 0.34101 MOTU_03 1.55005
MOTU_06 0.037100 0.16695 MOTU_04 2.73593
MOTU_07 0.000000 0.00000 MOTU_12 0.67115
MOTU_08 0.000000 0.00000 MOTU_03 4.51779
MOTU_09 0.000000 0.00000 MOTU_01 7.68126
MOTU_10 0.083475 0.16695 MOTU_02 0.67024
MOTU_11 0.000000 0.00000 MOTU_16 3.98825
MOTU_12 0.000000 0.00000 MOTU_07 0.67115
MOTU_13 0.000000 0.00000 MOTU_08 6.33176
MOTU_14 0.000000 0.00000 MOTU_15 11.60407
MOTU_15 0.000000 0.00000 MOTU_01 6.77516
MOTU_16 0.000000 0.00000 MOTU_11 3.98825
MOTU_17 NaN NaN MOTU_10 2.90372
MOTU_18 NaN NaN MOTU_08 7.47916

Analyzing data using ABGD species delimitation¶

In [13]:
ABGD=SPdel.run_ABGD(basepath,Inputs)
       groups         P
ABGD_1     27  0.001000
ABGD_2     27  0.001670
ABGD_3     19  0.002780
ABGD_4     18  0.004640
ABGD_5     16  0.007740
ABGD_6     16  0.012900
ABGD_7     15  0.021544

#####################
ABGD MOTUs
#####################

#####MOTU_01#####
LS_brn_L930, LS_brn_L931, LS_brn_L932

#####MOTU_02#####
LS_con_L210, LS_con_L211

#####MOTU_03#####
LS_con_L286, LS_con_L291, LS_con_L292, LS_con_L820

#####MOTU_04#####
LS_elo_L1041, LS_elo_L1046, LS_elo_L1047, LS_elo_L287, LS_elo_L300, LS_elo_L305, LS_elo_L307, LS_elo_L308, LS_elo_L309

#####MOTU_05#####
LS_gar_L293, LS_gar_L294, LS_gar_L295, LS_gar_L296, LS_gar_L298

#####MOTU_06#####
LS_mac_B061, LS_mac_B086, LS_mac_B087, LS_mac_B088, LS_mac_B089

#####MOTU_07#####
LS_muy_L907

#####MOTU_08#####
LS_muy_L913, LS_muy_L914, LS_muy_L915

#####MOTU_09#####
LS_obt_B031, LS_obt_B070, LS_obt_B071, LS_obt_B090, LS_obt_L253, LS_obt_L266, LS_obt_L267, LS_obt_L268, LS_obt_L269, LS_obt_L314, LS_obt_L315, LS_obt_L316, LS_obt_L320

#####MOTU_10#####
LS_obt_B074, LS_obt_B075, LS_obt_B077, LS_obt_B100, LS_obt_B101, LS_obt_B102, LS_obt_B103, LS_obt_L004, LS_obt_L007, LS_obt_L008, LS_obt_L009, LS_obt_L013, LS_obt_L016, LS_obt_L282, LS_obt_L283, LS_obt_L547, LS_obt_L548

#####MOTU_11#####
LS_obt_L084

#####MOTU_12#####
LS_piv_B060, LS_piv_B076, LS_piv_B078, LS_piv_B093, LS_piv_B094, LS_piv_B095, LS_piv_B096, LS_piv_B097, LS_piv_B098, LS_piv_B099, LS_piv_B140, LS_piv_B141, LS_piv_B142, LS_piv_B144, LS_piv_L002, LS_piv_L003, LS_piv_L005, LS_piv_L006, LS_piv_L010, LS_piv_L011, LS_piv_L014, LS_piv_L284, LS_piv_L371

#####MOTU_13#####
LS_rei_B072, LS_rei_B073, LS_rei_L338, LS_rei_L339, LS_rei_L341, LS_rei_L342, LS_rei_L343, LS_rei_L353, LS_rei_L355, LS_rei_L773, LS_rei_L777, LS_rei_L778, LS_rei_L779

#####MOTU_14#####
LS_tri_L179, LS_tri_L180, LS_tri_L182

#####MOTU_15#####
LS_tri_L519, LS_tri_L618, LS_tri_L621, LS_tri_L690, LS_tri_L955

#####MOTU_16#####
LS_mac_B082, LS_mac_L083, LS_mac_L085, LS_mac_L178, LS_mac_L212, LS_mac_L225, LS_mac_L290, LS_mac_L890, LS_mac_L891


Using k2p distance

In [14]:
ABGD.print_summary()
Out[14]:
Mean Max NN DtoNN
MOTU_01 0.000000 0.00000 MOTU_10 6.77516
MOTU_02 0.000000 0.00000 MOTU_03 3.98825
MOTU_03 0.000000 0.00000 MOTU_02 3.98825
MOTU_04 0.037100 0.16695 MOTU_09 2.73593
MOTU_05 0.000000 0.00000 MOTU_10 7.68126
MOTU_06 0.136404 0.34101 MOTU_16 1.55005
MOTU_07 NaN NaN MOTU_15 7.47916
MOTU_08 0.000000 0.00000 MOTU_01 11.60407
MOTU_09 0.000000 0.00000 MOTU_04 2.73593
MOTU_10 0.143081 0.50167 MOTU_09 2.84291
MOTU_11 NaN NaN MOTU_12 2.90372
MOTU_12 0.266286 1.00758 MOTU_11 2.90372
MOTU_13 0.316828 0.70177 MOTU_03 6.14484
MOTU_14 0.000000 0.00000 MOTU_15 6.33176
MOTU_15 0.000000 0.00000 MOTU_16 4.51779
MOTU_16 0.000000 0.00000 MOTU_06 1.55005

Analyzing data using ASAP species delimitation¶

In [15]:
ASAP=SPdel.run_ASAP(basepath,Inputs)
        groups  ASAPscores
ASAP_1      24         7.5
ASAP_2      19         6.5
ASAP_3      18         4.5
ASAP_4      17         7.5
ASAP_5      16         2.0
ASAP_6      15         1.5
ASAP_7      15         9.5
ASAP_8      13         5.0
ASAP_9      12         3.5
ASAP_10      7        11.0

#####################
ASAP MOTUs
#####################

#####MOTU_01#####
LS_brn_L930, LS_brn_L931, LS_brn_L932

#####MOTU_02#####
LS_con_L210, LS_con_L211

#####MOTU_03#####
LS_con_L286, LS_con_L291, LS_con_L292, LS_con_L820

#####MOTU_04#####
LS_elo_L1041, LS_elo_L1046, LS_elo_L1047, LS_elo_L300, LS_elo_L305, LS_elo_L307, LS_elo_L308, LS_elo_L309, LS_elo_L287

#####MOTU_05#####
LS_obt_B031, LS_obt_B070, LS_obt_B071, LS_obt_B090, LS_obt_L253, LS_obt_L266, LS_obt_L267, LS_obt_L268, LS_obt_L269, LS_obt_L314, LS_obt_L315, LS_obt_L316, LS_obt_L320

#####MOTU_06#####
LS_obt_B074, LS_obt_B075, LS_obt_B077, LS_obt_L004, LS_obt_L007, LS_obt_L009, LS_obt_L013, LS_obt_L016, LS_obt_L282, LS_obt_L283, LS_obt_L547, LS_obt_L548, LS_obt_L008, LS_obt_B100, LS_obt_B101, LS_obt_B102, LS_obt_B103

#####MOTU_07#####
LS_obt_L084

#####MOTU_08#####
LS_piv_B060, LS_piv_B076, LS_piv_B078, LS_piv_B093, LS_piv_B094, LS_piv_B095, LS_piv_L002, LS_piv_L003, LS_piv_L005, LS_piv_L006, LS_piv_L010, LS_piv_L011, LS_piv_L014, LS_piv_L284, LS_piv_L371, LS_piv_B096, LS_piv_B097, LS_piv_B098, LS_piv_B099, LS_piv_B140, LS_piv_B141, LS_piv_B142, LS_piv_B144

#####MOTU_09#####
LS_rei_B072, LS_rei_B073, LS_rei_L338, LS_rei_L339, LS_rei_L341, LS_rei_L342, LS_rei_L343, LS_rei_L353, LS_rei_L355, LS_rei_L773, LS_rei_L777, LS_rei_L778, LS_rei_L779

#####MOTU_10#####
LS_gar_L293, LS_gar_L294, LS_gar_L295, LS_gar_L296, LS_gar_L298

#####MOTU_11#####
LS_mac_B061, LS_mac_B086, LS_mac_B087, LS_mac_B088, LS_mac_B089, LS_mac_B082, LS_mac_L083, LS_mac_L085, LS_mac_L178, LS_mac_L212, LS_mac_L225, LS_mac_L290, LS_mac_L890, LS_mac_L891

#####MOTU_12#####
LS_tri_L519, LS_tri_L618, LS_tri_L621, LS_tri_L690, LS_tri_L955

#####MOTU_13#####
LS_tri_L179, LS_tri_L180, LS_tri_L182

#####MOTU_14#####
LS_muy_L907

#####MOTU_15#####
LS_muy_L913, LS_muy_L914, LS_muy_L915


Using k2p distance

In [16]:
ASAP.print_summary()
Out[16]:
Mean Max NN DtoNN
MOTU_01 0.000000 0.00000 MOTU_06 6.77516
MOTU_02 0.000000 0.00000 MOTU_03 3.98825
MOTU_03 0.000000 0.00000 MOTU_02 3.98825
MOTU_04 0.037100 0.16695 MOTU_05 2.73593
MOTU_05 0.000000 0.00000 MOTU_04 2.73593
MOTU_06 0.143081 0.50167 MOTU_05 2.84291
MOTU_07 NaN NaN MOTU_08 2.90372
MOTU_08 0.266286 1.00758 MOTU_07 2.90372
MOTU_09 0.316828 0.70177 MOTU_03 6.14484
MOTU_10 0.000000 0.00000 MOTU_06 7.68126
MOTU_11 0.903538 1.85854 MOTU_12 4.51779
MOTU_12 0.000000 0.00000 MOTU_11 4.51779
MOTU_13 0.000000 0.00000 MOTU_12 6.33176
MOTU_14 NaN NaN MOTU_12 7.47916
MOTU_15 0.000000 0.00000 MOTU_01 11.60407

Analyzing data using any species delimitation precalculate from a csv file¶

In [17]:
csv_file= './data/Megaleporinus/BIN_list.csv'
In [18]:
csv_motus=SPdel.run_csvList(basepath,Inputs,csv_file)
#####################
BIN MOTUs
#####################

#####MOTU_AAB8569#####
LS_piv_B060, LS_piv_B076, LS_piv_B078, LS_piv_B093, LS_piv_B094, LS_piv_B095, LS_piv_B096, LS_piv_B097, LS_piv_B098, LS_piv_B099, LS_piv_B140, LS_piv_B141, LS_piv_B142, LS_piv_B144, LS_piv_L002, LS_piv_L003, LS_piv_L005, LS_piv_L006, LS_piv_L010, LS_piv_L011, LS_piv_L014, LS_piv_L284, LS_piv_L371

#####MOTU_AAB8578#####
LS_obt_B074, LS_obt_B075, LS_obt_B077, LS_obt_B100, LS_obt_B101, LS_obt_B102, LS_obt_B103, LS_obt_L004, LS_obt_L007, LS_obt_L008, LS_obt_L009, LS_obt_L013, LS_obt_L016, LS_obt_L282, LS_obt_L283, LS_obt_L547, LS_obt_L548

#####MOTU_AAD1729#####
LS_rei_B072, LS_rei_B073, LS_rei_L338, LS_rei_L339, LS_rei_L341, LS_rei_L342, LS_rei_L343, LS_rei_L353, LS_rei_L355, LS_rei_L773, LS_rei_L777, LS_rei_L778, LS_rei_L779

#####MOTU_AAE5328#####
LS_mac_B082, LS_mac_L083, LS_mac_L085, LS_mac_L178, LS_mac_L212, LS_mac_L225, LS_mac_L290, LS_mac_L890, LS_mac_L891

#####MOTU_ABY2894#####
LS_elo_L1041, LS_elo_L1046, LS_elo_L1047, LS_elo_L287, LS_elo_L300, LS_elo_L305, LS_elo_L307, LS_elo_L308, LS_elo_L309

#####MOTU_ABZ0928#####
LS_obt_B031, LS_obt_B070, LS_obt_B071, LS_obt_B090, LS_obt_L253, LS_obt_L266, LS_obt_L267, LS_obt_L268, LS_obt_L269, LS_obt_L314, LS_obt_L315, LS_obt_L316, LS_obt_L320

#####MOTU_ACL3073#####
LS_tri_L519, LS_tri_L618, LS_tri_L621, LS_tri_L690, LS_tri_L955

#####MOTU_ACL3074#####
LS_tri_L179, LS_tri_L180, LS_tri_L182

#####MOTU_ACL3227#####
LS_gar_L293, LS_gar_L294, LS_gar_L295, LS_gar_L296, LS_gar_L298

#####MOTU_ACL3731#####
LS_con_L210, LS_con_L211

#####MOTU_ACL3942#####
LS_obt_L084

#####MOTU_ACL4264#####
LS_con_L286, LS_con_L291, LS_con_L292, LS_con_L820

#####MOTU_ACO1303#####
LS_mac_B061, LS_mac_B086, LS_mac_B087, LS_mac_B088, LS_mac_B089

#####MOTU_ADB0463#####
LS_brn_L930, LS_brn_L931, LS_brn_L932

#####MOTU_ADB0512#####
LS_muy_L907

#####MOTU_ADB0701#####
LS_muy_L913, LS_muy_L914, LS_muy_L915


Using k2p distance

In [19]:
csv_motus['BIN'].print_summary()
Out[19]:
Mean Max NN DtoNN
MOTU_AAB8569 0.266286 1.00758 MOTU_ACL3942 2.90372
MOTU_AAB8578 0.143081 0.50167 MOTU_ABZ0928 2.84291
MOTU_AAD1729 0.316828 0.70177 MOTU_ACL4264 6.14484
MOTU_AAE5328 0.000000 0.00000 MOTU_ACO1303 1.55005
MOTU_ABY2894 0.037100 0.16695 MOTU_ABZ0928 2.73593
MOTU_ABZ0928 0.000000 0.00000 MOTU_ABY2894 2.73593
MOTU_ACL3073 0.000000 0.00000 MOTU_AAE5328 4.51779
MOTU_ACL3074 0.000000 0.00000 MOTU_ACL3073 6.33176
MOTU_ACL3227 0.000000 0.00000 MOTU_AAB8578 7.68126
MOTU_ACL3731 0.000000 0.00000 MOTU_ACL4264 3.98825
MOTU_ACL3942 NaN NaN MOTU_AAB8569 2.90372
MOTU_ACL4264 0.000000 0.00000 MOTU_ACL3731 3.98825
MOTU_ACO1303 0.136404 0.34101 MOTU_AAE5328 1.55005
MOTU_ADB0463 0.000000 0.00000 MOTU_AAB8578 6.77516
MOTU_ADB0512 NaN NaN MOTU_ACL3073 7.47916
MOTU_ADB0701 0.000000 0.00000 MOTU_ADB0463 11.60407

Comparing the different species delimitation results¶

In [20]:
Compare_list = 'All'
In [21]:
compared=SPdel.run_comparison(basepath,Inputs,Compare_list)
#####################
 Consensus MOTUs
#####################

### MOTU totally matching the taxonomy ###

Consensus MOTU 01 [LS_brn_(Nominal)&MOTU_01_(ABGD)&MOTU_01_(ASAP)&MOTU_ADB0463_(BIN)&MOTU_03_(bPTP)&MOTU_15_(GMYC)&MOTU_03_(mPTP)&MOTU_03_(PTP)]
LS_brn_L930, LS_brn_L931, LS_brn_L932

Consensus MOTU 02 [LS_elo_(Nominal)&MOTU_04_(ABGD)&MOTU_04_(ASAP)&MOTU_ABY2894_(BIN)&MOTU_10_(bPTP)&MOTU_06_(GMYC)&MOTU_04_(mPTP)&MOTU_10_(PTP)]
LS_elo_L1041, LS_elo_L1046, LS_elo_L1047, LS_elo_L287, LS_elo_L300, LS_elo_L305, LS_elo_L307, LS_elo_L308, LS_elo_L309

Consensus MOTU 03 [LS_gar_(Nominal)&MOTU_05_(ABGD)&MOTU_10_(ASAP)&MOTU_ACL3227_(BIN)&MOTU_04_(bPTP)&MOTU_09_(GMYC)&MOTU_09_(mPTP)&MOTU_04_(PTP)]
LS_gar_L293, LS_gar_L294, LS_gar_L295, LS_gar_L296, LS_gar_L298

### MOTU mostly matching the taxonomy ###

Consensus MOTU 04 [LS_piv_(Nominal)&MOTU_12_(ABGD)&MOTU_08_(ASAP)&MOTU_AAB8569_(BIN)&MOTU_07_(mPTP)]
LS_piv_B060, LS_piv_B076, LS_piv_B078, LS_piv_B093, LS_piv_B094, LS_piv_B095, LS_piv_B096, LS_piv_B097, LS_piv_B098, LS_piv_B099, LS_piv_B140, LS_piv_B141, LS_piv_B142, LS_piv_B144, LS_piv_L002, LS_piv_L003, LS_piv_L005, LS_piv_L006, LS_piv_L010, LS_piv_L011, LS_piv_L014, LS_piv_L284, LS_piv_L371

### MOTU totally mismatching the taxonomy ###

Consensus MOTU 05 [MOTU_02_(ABGD)&MOTU_02_(ASAP)&MOTU_ACL3731_(BIN)&MOTU_07_(bPTP)&MOTU_16_(GMYC)&MOTU_02_(mPTP)&MOTU_07_(PTP)]
LS_con_L210, LS_con_L211

Consensus MOTU 06 [MOTU_03_(ABGD)&MOTU_03_(ASAP)&MOTU_ACL4264_(BIN)&MOTU_06_(bPTP)&MOTU_11_(GMYC)&MOTU_01_(mPTP)&MOTU_06_(PTP)]
LS_con_L286, LS_con_L291, LS_con_L292, LS_con_L820

Consensus MOTU 07 [MOTU_07_(ABGD)&MOTU_14_(ASAP)&MOTU_ADB0512_(BIN)&MOTU_02_(bPTP)&MOTU_18_(GMYC)&MOTU_13_(mPTP)&MOTU_02_(PTP)]
LS_muy_L907

Consensus MOTU 08 [MOTU_08_(ABGD)&MOTU_15_(ASAP)&MOTU_ADB0701_(BIN)&MOTU_01_(bPTP)&MOTU_14_(GMYC)&MOTU_12_(mPTP)&MOTU_01_(PTP)]
LS_muy_L913, LS_muy_L914, LS_muy_L915

Consensus MOTU 09 [MOTU_09_(ABGD)&MOTU_05_(ASAP)&MOTU_ABZ0928_(BIN)&MOTU_11_(bPTP)&MOTU_04_(GMYC)&MOTU_05_(mPTP)&MOTU_11_(PTP)]
LS_obt_B031, LS_obt_B070, LS_obt_B071, LS_obt_B090, LS_obt_L253, LS_obt_L266, LS_obt_L267, LS_obt_L268, LS_obt_L269, LS_obt_L314, LS_obt_L315, LS_obt_L316, LS_obt_L320

Consensus MOTU 10 [MOTU_10_(ABGD)&MOTU_06_(ASAP)&MOTU_AAB8578_(BIN)&MOTU_09_(bPTP)&MOTU_01_(GMYC)&MOTU_06_(mPTP)&MOTU_09_(PTP)]
LS_obt_B074, LS_obt_B075, LS_obt_B077, LS_obt_B100, LS_obt_B101, LS_obt_B102, LS_obt_B103, LS_obt_L004, LS_obt_L007, LS_obt_L008, LS_obt_L009, LS_obt_L013, LS_obt_L016, LS_obt_L282, LS_obt_L283, LS_obt_L547, LS_obt_L548

Consensus MOTU 11 [MOTU_11_(ABGD)&MOTU_07_(ASAP)&MOTU_ACL3942_(BIN)&MOTU_12_(bPTP)&MOTU_17_(GMYC)&MOTU_08_(mPTP)&MOTU_12_(PTP)]
LS_obt_L084

Consensus MOTU 12 [MOTU_14_(ABGD)&MOTU_13_(ASAP)&MOTU_ACL3074_(BIN)&MOTU_05_(bPTP)&MOTU_13_(GMYC)&MOTU_14_(mPTP)&MOTU_05_(PTP)]
LS_tri_L179, LS_tri_L180, LS_tri_L182

Consensus MOTU 13 [MOTU_15_(ABGD)&MOTU_12_(ASAP)&MOTU_ACL3073_(BIN)&MOTU_08_(bPTP)&MOTU_08_(GMYC)&MOTU_17_(mPTP)&MOTU_08_(PTP)]
LS_tri_L519, LS_tri_L618, LS_tri_L621, LS_tri_L690, LS_tri_L955

### MOTUs mostly mismatching the taxonomy ###

Consensus MOTU 14 [MOTU_06_(ABGD)&MOTU_ACO1303_(BIN)&MOTU_13_(bPTP)&MOTU_05_(GMYC)&MOTU_15_(mPTP)&MOTU_13_(PTP)]
LS_mac_B061, LS_mac_B086, LS_mac_B087, LS_mac_B088, LS_mac_B089

Consensus MOTU 15 [MOTU_16_(ABGD)&MOTU_AAE5328_(BIN)&MOTU_14_(bPTP)&MOTU_03_(GMYC)&MOTU_16_(mPTP)&MOTU_14_(PTP)]
LS_mac_B082, LS_mac_L083, LS_mac_L085, LS_mac_L178, LS_mac_L212, LS_mac_L225, LS_mac_L290, LS_mac_L890, LS_mac_L891

Consensus MOTU 16 [MOTU_15_(bPTP)&MOTU_12_(GMYC)&MOTU_10_(mPTP)&MOTU_15_(PTP)]
LS_rei_L773, LS_rei_L777, LS_rei_L778, LS_rei_L779

Consensus MOTU 17 [MOTU_16_(bPTP)&MOTU_07_(GMYC)&MOTU_11_(mPTP)&MOTU_16_(PTP)]
LS_rei_B072, LS_rei_L342, LS_rei_B073, LS_rei_L341, LS_rei_L338, LS_rei_L355, LS_rei_L339, LS_rei_L343, LS_rei_L353

Using k2p distance

In [22]:
SPdel.plot_compare_tree(basepath, Inputs.tree, compared[0])
#####
Warning: Nominal species not contigous in the tree.
#####

LS_obt_L315LS_obt_L314LS_obt_L320LS_obt_L253LS_obt_L269LS_obt_L267LS_obt_B071LS_obt_L316LS_obt_L266LS_obt_L268LS_obt_B070LS_obt_B090LS_obt_B031LS_elo_L305LS_elo_L300LS_elo_L1046LS_elo_L309LS_elo_L287LS_elo_L1041LS_elo_L308LS_elo_L307LS_elo_L1047LS_obt_L013LS_obt_L004LS_obt_L283LS_obt_L548LS_obt_L009LS_obt_B075LS_obt_L016LS_obt_B074LS_obt_B077LS_obt_L547LS_obt_L282LS_obt_L008LS_obt_L007LS_obt_B102LS_obt_B101LS_obt_B103LS_obt_B100LS_piv_L014LS_piv_L006LS_piv_L005LS_piv_B078LS_piv_L284LS_piv_B094LS_piv_B076LS_piv_L371LS_piv_L011LS_piv_L003LS_piv_L002LS_piv_L010LS_piv_B095LS_piv_B060LS_piv_B093LS_piv_B098LS_piv_B097LS_piv_B096LS_piv_B099LS_piv_B142LS_piv_B141LS_piv_B144LS_piv_B140LS_obt_L084LS_gar_L296LS_gar_L294LS_gar_L295LS_gar_L298LS_gar_L293LS_brn_L932LS_brn_L931LS_brn_L930LS_con_L292LS_con_L291LS_con_L820LS_con_L286LS_con_L211LS_con_L210LS_rei_L355LS_rei_L338LS_rei_L341LS_rei_B073LS_rei_L342LS_rei_B072LS_rei_L353LS_rei_L343LS_rei_L339LS_rei_L779LS_rei_L778LS_rei_L777LS_rei_L773LS_muy_L915LS_muy_L913LS_muy_L914LS_mac_L891LS_mac_L212LS_mac_L225LS_mac_L178LS_mac_L085LS_mac_L083LS_mac_L890LS_mac_B082LS_mac_L290LS_mac_B088LS_mac_B087LS_mac_B089LS_mac_B086LS_mac_B061LS_tri_L955LS_tri_L618LS_tri_L690LS_tri_L519LS_tri_L621LS_tri_L182LS_tri_L180LS_tri_L179LS_muy_L907NominalABGDASAPBINbPTPGMYCmPTPPTPConsensusNominalABGDASAPBINbPTPGMYCmPTPPTPConsensusNominalABGDASAPBINbPTPGMYCmPTPPTPConsensusNominalABGDASAPBINbPTPGMYCmPTPPTPConsensusNominalABGDASAPBINbPTPGMYCmPTPPTPConsensusNominalABGDASAPBINbPTPGMYCmPTPPTPConsensusNominalABGDASAPBINbPTPGMYCmPTPPTPConsensusNominalABGDASAPBINbPTPGMYCmPTPPTPConsensusNominalABGDASAPBINbPTPGMYCmPTPPTPConsensus035810131518

Saving tree plot as svg

In [23]:
SPdel.plot_compare_tree(basepath, Inputs.tree, compared[0],save=True)
#####
Warning: Nominal species not contigous in the tree.
#####

In [24]:
compared[1].print_summary()
Out[24]:
Mean Max NN DtoNN
MOTU_01 0.000000 0.00000 MOTU_10 6.77516
MOTU_02 0.037100 0.16695 MOTU_09 2.73593
MOTU_03 0.000000 0.00000 MOTU_10 7.68126
MOTU_04 0.266286 1.00758 MOTU_11 2.90372
MOTU_05 0.000000 0.00000 MOTU_06 3.98825
MOTU_06 0.000000 0.00000 MOTU_05 3.98825
MOTU_07 NaN NaN MOTU_13 7.47916
MOTU_08 0.000000 0.00000 MOTU_01 11.60407
MOTU_09 0.000000 0.00000 MOTU_02 2.73593
MOTU_10 0.143081 0.50167 MOTU_09 2.84291
MOTU_11 NaN NaN MOTU_04 2.90372
MOTU_12 0.000000 0.00000 MOTU_13 6.33176
MOTU_13 0.000000 0.00000 MOTU_15 4.51779
MOTU_14 0.136404 0.34101 MOTU_15 1.55005
MOTU_15 0.000000 0.00000 MOTU_14 1.55005
MOTU_16 0.000000 0.00000 MOTU_17 0.67115
MOTU_17 0.000000 0.00000 MOTU_16 0.67115
In [25]:
compared[1].plot_max_min()
In [26]:
compared[1].plot_freq() 
In [27]:
compared[1].plot_heatmap(upper=4) 

Thanks for use SPdel!